PhD Position in Physical Computing and Learning in Soft Matter

Are you fascinated by the emergence of intelligence in materials? Join our interdisciplinary research team at Utrecht University to explore how simple building blocks can exhibit learning behavior. This fully-funded PhD position offers a unique opportunity to work at the forefront of physics, materials science, and computation.

Your job

The Emergence at all Scales (EAAS) consortium is the national flagship of the Dutch Institute for Emergent Phenomena (D-IEP), a game-changer in the NWA Route 2 initiative. EAAS unites eight Dutch universities, one Ukrainian university, and Statistics Netherlands (CBS) in an interdisciplinary effort to understand emergent phenomena across scales. Our research combines multiple fields including physics, mathematics, astronomy, history & philosophy of science, and social science. Its approach to societal engagement throughout the project’s five-year lifetime is equally interdisciplinary, with a wide variety of activities ranging from art/science programmes, large scale science festivals, citizen science and educational initiatives at various levels.EAAS is hiring 20 PhD/postdoc researchers across various fields, and we are committed to achieving gender parity in our recruitment. We now invite applications for a PhD position in the sub-project "Intelligent Matter", led by Professor Marjolein Dijkstra in the Soft Condensed Matter (SCM) group at the Debye Institute for Nanomaterials Science , Utrecht University. The position is offered in collaboration with Peter Bolhuis (UvA/chemistry), René van Roij (UU/physics), Martin van Hecke (AMOLF/UL/physics), Corentin Coulais (UvA/physics), Senja Barthel (VU/mathematics).This project aims to explore the emergence of intelligent behaviour in materials composed of simple building blocks, such as water, ions, molecular receptors, lipids, and colloids. Using theory and simulations, we seek to understand how collective interactions lead to self-organised learning behaviours. From understanding the mechanisms for “learning”, leveraging topological defects in liquid crystals for information processing, to the hydrodynamic description of water and ion transport through neuromorphic networks, we aim to design materials with learning capabilities. Our approach involves exploring multistability, hysteresis, and non-linearity in soft materials for memory, learning, and computation. By systematically designing simplified models and conditions, we aim to understand and control emergent dynamic properties, and to gain insight into the emergence of cognitive functions and intelligent behaviour across various systems. This will enable us to create learning behaviour in cutting-edge materials. This pursuit may lead to smarter materials capable of storing and processing information, and even performing computations.

Your qualities

You are highly motivated and have:

• a Master's degree or an international equivalent in theoretical or computational physics (or a related field);
• a strong background in statistical physics, soft matter, and programming in e.g. C or C++, python, LAMPPS;
• perseverance and an independent, pro-active working style;
• the willingness to look beyond the borders of their own discipline and a strong motivation to work in a multidisciplinary team;
• excellent collaboration and communication skills (written and verbally) in English.

Our offer

We offer:

• a position for four years;
• a fulltime working week and a gross monthly salary between €2,901 and €3,707 in the case of full-time employment (salary scale P under the Collective Labour Agreement for Dutch Universities (CAO NU));
• 8% holiday pay and 8.3% year-end bonus;
• a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.